An object detecting device has been known that calculates a displacement (disparity) between stereo images (a target image and a reference image) by stereo matching of the target image and the reference image, and detects an object on the basis of the calculated disparity. An example application under study of the object detecting device is a system that can detect objects (i.e., three-dimensional objects such as vehicles and pedestrians other than the road surface) and road surfaces, in stereo images, captured by a vehicle-mounted camera, of a view in front of a vehicle.
A proposed conventional object detecting device calculates the slope of the height direction of the object candidate captured in the stereo images, and identifies as a real object or a road surface from the calculated slope (see PTL 1, for example).
FIG. 1 is a block diagram illustrating the configuration of an object detecting device described in PTL 1.
As shown in FIG. 1, object detecting device 10 includes stereo image acquiring unit 11, disparity map generator 12, road surface estimator 13, object candidate location extractor 14, and slope calculating and determining unit 15.
Stereo image acquiring unit 11 acquires a pair of stereo images that are simultaneously captured by a stereo camera having two lenses arranged horizontally.
Disparity map generator 12 generates a disparity map on the basis of the stereo images acquired by stereo image acquiring unit 11. The disparity map is obtained through calculation of a displacement (disparity) between a target image and a reference image for every pixel by stereo matching.
Road surface estimator 13 estimates a road surface on the basis of the disparity map generated by disparity map generator 12.
Object candidate location extractor 14 extracts regions where spaces above the road surface estimated by road surface estimator 13 in a real space are imaged, on the basis of the disparity map generated by disparity map generator 12. Object candidate location extractor 14 classifies the extracted regions into groups, the extracted regions of each group having approximate disparity values, and extracts regions looking like objects (referred to hereafter as “object candidates”) from the stereo images.
Slope calculating and determining unit 15 calculates the slope of the disparity in the vertical direction of the region where the object candidate extracted by object candidate location extractor 14 (i.e., the slope in the height direction of the object candidate) is imaged, on the basis of the disparity map generated by disparity map generator 12, and identifies the object candidate as a real object or a road surface. Specifically, slope determining unit 15 determines that the object candidate is a real object if the slope of disparity is greater than a predetermined threshold, while it determines that the object candidate is a road surface if the slope of disparity is less than the predetermined threshold.
A target identifying device described in PTL 2 calculates the deviation of disparity values in a depth direction and the deviation of disparity values in a vertical direction on the basis of the disparity of the region of the stereo images where an object candidate is captured, and identifies the object candidate as a real object or a road surface.